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Autor/inn/enLeite, Walter L.; Sandbach, Robert; Jin, Rong; MacInnes, Jann W.; Jackman, M. Grace-Anne
TitelAn Evaluation of Latent Growth Models for Propensity Score Matched Groups
QuelleIn: Structural Equation Modeling: A Multidisciplinary Journal, 19 (2012) 3, S.437-456 (20 Seiten)
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1070-5511
DOI10.1080/10705511.2012.687666
SchlagwörterStructural Equation Models; Probability; Computation; Observation; Longitudinal Studies; Matched Groups; Monte Carlo Methods; Goodness of Fit; Statistical Bias; Error of Measurement; Statistical Analysis; Elementary School Students; Transfer Students; Reading Achievement; Mathematics Achievement; Poverty; Early Childhood Longitudinal Survey
AbstractBecause random assignment is not possible in observational studies, estimates of treatment effects might be biased due to selection on observable and unobservable variables. To strengthen causal inference in longitudinal observational studies of multiple treatments, we present 4 latent growth models for propensity score matched groups, and evaluate their performance with a Monte Carlo simulation study. We found that the 4 models performed similarly with respect to model fit, bias of parameter estimates, Type I error, and power to test the treatment effect. To demonstrate a multigroup latent growth model with dummy treatment indicators, we estimated the effect of students changing schools during elementary school years on their reading and mathematics achievement, using data from the Early Childhood Longitudinal Study Kindergarten Cohort. (Contains 4 tables and 1 figure.) (As Provided).
AnmerkungenPsychology Press. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2017/4/10
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